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BACKGROUND: Individuals with a Fontan circulation encompass a heterogeneous group with adverse outcomes linked to ventricular dilation, dysfunction, and dyssynchrony. The purpose of this study was to assess if unsupervised machine learning cluster analysis of cardiovascular magnetic resonance (CMR)-derived dyssynchrony metrics can separate ventricles in the Fontan circulation from normal control left ventricles and identify prognostically distinct subgroups within the Fontan cohort. METHODS: This single-center, retrospective study used 503 CMR studies from Fontan patients (median age 15 y) and 42 from age-matched controls from January 2005 to May 2011. Feature tracking on short-axis cine stacks assessed radial and circumferential strain, strain rate, and displacement. Unsupervised K-means clustering was applied to 24 mechanical dyssynchrony metrics derived from these deformation measurements. Clusters were compared for demographic, anatomical, and composite outcomes of death, or heart transplantation. RESULTS: Four distinct phenotypic clusters were identified. Over a median follow-up of 4.2 y (interquartile ranges 1.7-8.8 y), 58 (11.5%) patients met the composite outcome. The highest-risk cluster (largely comprised of right or mixed ventricular morphology and dilated, dyssynchronous ventricles) exhibited a higher hazard for the composite outcome compared to the lowest-risk cluster while controlling for ventricular morphology (hazard ratio [HR] 6.4; 95% confidence interval [CI] 2.1-19.3; P value 0.001) and higher indexed end-diastolic volume (HR 3.2; 95% CI 1.04-10.0; P value 0.043) per 10 mL/m2. CONCLUSION: Unsupervised machine learning using CMR-derived dyssynchrony metrics identified four distinct clusters of patients with Fontan circulation and healthy controls with varying clinical characteristics and risk profiles. This technique can be used to guide future studies and identify more homogeneous subsets of patients from an overall heterogeneous population.
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BACKGROUND AND AIMS: The gut microbiota contributes to aberrant inflammation in inflammatory bowel disease, but the bacterial factors causing or exacerbating inflammation are not fully understood. Further, the predictive or prognostic value of gut microbial biomarkers for remission in response to biologic therapy is unclear. METHODS: We perform whole metagenomic sequencing of 550 stool samples from 287 ulcerative colitis patients from a large phase 3 head-to-head study of infliximab and etrolizumab. RESULTS: We identify several bacterial species in baseline and/or post-treatment samples that associate with clinical remission. These include previously described associations (Faecalibacterium prausnitzii_F) as well as new associations with remission to biologic therapy (Flavonifractor plautii). We build multivariate models and find that gut microbial species are better predictors for remission than clinical variables alone. Finally, we describe patient groups that differ in microbiome composition and remission rate after induction therapy, suggesting the potential utility of microbiome-based endotyping. CONCLUSIONS: In this large study of ulcerative colitis patients, we show that few individual species associate strongly with clinical remission, but multivariate models including microbiome can predict clinical remission and have better predictive power compared to clinical data alone.
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Medulloblastomas with extensive nodularity are cerebellar tumors characterized by two distinct compartments and variable disease progression. The mechanisms governing the balance between proliferation and differentiation in MBEN remain poorly understood. Here, we employ a multi-modal single cell transcriptome analysis to dissect this process. In the internodular compartment, we identify proliferating cerebellar granular neuronal precursor-like malignant cells, along with stromal, vascular, and immune cells. In contrast, the nodular compartment comprises postmitotic, neuronally differentiated malignant cells. Both compartments are connected through an intermediate cell stage resembling actively migrating CGNPs. Notably, we also discover astrocytic-like malignant cells, found in proximity to migrating and differentiated cells at the transition zone between the two compartments. Our study sheds light on the spatial tissue organization and its link to the developmental trajectory, resulting in a more benign tumor phenotype. This integrative approach holds promise to explore intercompartmental interactions in other cancers with varying histology.
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Neoplasias Cerebelares , Meduloblastoma , Humanos , Meduloblastoma/genética , Diferenciação Celular , Neoplasias Cerebelares/genética , Progressão da Doença , Técnicas HistológicasRESUMO
Many genes that drive normal cellular development also contribute to oncogenesis. Medulloblastoma (MB) tumors likely arise from neuronal progenitors in the cerebellum, and we hypothesized that the heterogeneity observed in MBs with sonic hedgehog (SHH) activation could be due to differences in developmental pathways. To investigate this question, here we perform single-nucleus RNA sequencing on highly differentiated SHH MBs with extensively nodular histology and observed malignant cells resembling each stage of canonical granule neuron development. Through innovative computational approaches, we connect these results to published datasets and find that some established molecular subtypes of SHH MB appear arrested at different developmental stages. Additionally, using multiplexed proteomic imaging and MALDI imaging mass spectrometry, we identify distinct histological and metabolic profiles for highly differentiated tumors. Our approaches are applicable to understanding the interplay between heterogeneity and differentiation in other cancers and can provide important insights for the design of targeted therapies.
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Neoplasias Cerebelares , Meduloblastoma , Humanos , Proteínas Hedgehog/genética , Meduloblastoma/genética , Proteômica , Cerebelo , Neoplasias Cerebelares/genéticaRESUMO
BACKGROUND: Ventricular dyssynchrony and its relationship to clinical outcomes is not well characterized in patients following Fontan palliation. METHODS: Single-center retrospective analysis of cardiac magnetic resonance (CMR) imaging of patients with a Fontan circulation and an age-matched healthy comparison cohort as controls. Feature tracking was performed on all slices of a ventricular short-axis cine stack. Circumferential and radial strain, strain rate, and displacement were measured; and multiple dyssynchrony metrics were calculated based on timing of these measurements (including standard deviation of time-to-peak, maximum opposing wall delay, and maximum base-to-apex delay). Primary endpoint was a composite measure including time to death, heart transplant or heart transplant listing (D/HTx). RESULTS: A total of 503 cases (15 y; IQR 10, 21) and 42 controls (16 y; IQR 11, 20) were analyzed. Compared to controls, Fontan patients had increased dyssynchrony metrics, longer QRS duration, larger ventricular volumes, and worse systolic function. Dyssynchrony metrics were higher in patients with right ventricular (RV) or mixed morphology compared to those with LV morphology. At median follow-up of 4.3 years, 11% had D/HTx. Multiple risk factors for D/HTx were identified, including RV morphology, ventricular dilation, dysfunction, QRS prolongation, and dyssynchrony. Ventricular dilation and RV morphology were independently associated with D/HTx. CONCLUSIONS: Compared to control LVs, single right and mixed morphology ventricles in the Fontan circulation exhibit a higher degree of mechanical dyssynchrony as evaluated by CMR-FT. Dyssynchrony indices correlate with ventricular size and function and are associated with death or need for heart transplantation. These data add to the growing understanding regarding factors that can be used to risk-stratify patients with the Fontan circulation.
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Técnica de Fontan , Humanos , Técnica de Fontan/efeitos adversos , Estudos Retrospectivos , Valor Preditivo dos Testes , Ventrículos do Coração , CoraçãoRESUMO
The lack of reliable predictive biomarkers to guide effective therapy is a major obstacle to the advancement of therapy for high-grade gliomas, particularly glioblastoma (GBM), one of the few cancers whose prognosis has not improved over the past several decades. With this pilot clinical trial (number NCT04135807), we provide first-in-human evidence that drug-releasing intratumoral microdevices (IMDs) can be safely and effectively used to obtain patient-specific, high-throughput molecular and histopathological drug response profiling. These data can complement other strategies to inform the selection of drugs based on their observed antitumor effect in situ. IMDs are integrated into surgical practice during tumor resection and remain in situ only for the duration of the otherwise standard operation (2 to 3 hours). None of the six enrolled patients experienced adverse events related to the IMD, and the exposed tissue was usable for downstream analysis for 11 out of 12 retrieved specimens. Analysis of the specimens provided preliminary evidence of the robustness of the readout, compatibility with a wide array of techniques for molecular tissue interrogation, and promising similarities with the available observed clinical-radiological responses to temozolomide. From an investigational aspect, the amount of information obtained with IMDs allows characterization of tissue effects of any drugs of interest, within the physiological context of the intact tumor, and without affecting the standard surgical workflow.
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Glioblastoma , Glioma , Humanos , Glioma/tratamento farmacológico , Sistemas de Liberação de Medicamentos , Liberação Controlada de Fármacos , Temozolomida/uso terapêuticoRESUMO
The complexity of affected brain regions and cell types is a challenge for Huntington's disease (HD) treatment. Here we use single nucleus RNA sequencing to investigate molecular pathology in the cortex and striatum from R6/2 mice and human HD post-mortem tissue. We identify cell type-specific and -agnostic signatures suggesting oligodendrocytes (OLs) and oligodendrocyte precursors (OPCs) are arrested in intermediate maturation states. OL-lineage regulators OLIG1 and OLIG2 are negatively correlated with CAG length in human OPCs, and ATACseq analysis of HD mouse NeuN-negative cells shows decreased accessibility regulated by OL maturation genes. The data implicates glucose and lipid metabolism in abnormal cell maturation and identify PRKCE and Thiamine Pyrophosphokinase 1 (TPK1) as central genes. Thiamine/biotin treatment of R6/1 HD mice to compensate for TPK1 dysregulation restores OL maturation and rescues neuronal pathology. Our insights into HD OL pathology spans multiple brain regions and link OL maturation deficits to abnormal thiamine metabolism.
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Biotina , Doença de Huntington , Oligodendroglia , Tiamina , Animais , Humanos , Camundongos , Biotina/metabolismo , Biotina/farmacologia , Suplementos Nutricionais , Modelos Animais de Doenças , Doença de Huntington/metabolismo , Camundongos Transgênicos , Proteínas do Tecido Nervoso/metabolismo , Oligodendroglia/metabolismo , Núcleo Solitário/metabolismo , Tiamina/metabolismo , Tiamina/farmacologiaRESUMO
When analyzing biological data, it can be helpful to consider gene sets, or predefined groups of biologically related genes. Methods exist for identifying gene sets that are differential between conditions, but large public datasets from consortium projects and single-cell RNA-Sequencing have opened the door for gene set analysis using more sophisticated machine learning techniques, such as autoencoders and variational autoencoders. We present shallow sparsely-connected autoencoders (SSCAs) and variational autoencoders (SSCVAs) as tools for projecting gene-level data onto gene sets. We tested these approaches on single-cell RNA-Sequencing data from blood cells and on RNA-Sequencing data from breast cancer patients. Both SSCA and SSCVA can recover known biological features from these datasets and the SSCVA method often outperforms SSCA (and six existing gene set scoring algorithms) on classification and prediction tasks.
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Perfilação da Expressão Gênica/estatística & dados numéricos , Redes Reguladoras de Genes , Análise de Sequência de RNA/estatística & dados numéricos , Células Sanguíneas/metabolismo , Neoplasias da Mama/genética , Neoplasias da Mama/mortalidade , Biologia Computacional , Feminino , Humanos , Redes Neurais de Computação , Análise de Célula Única/estatística & dados numéricos , Aprendizado de Máquina Supervisionado , Análise de SobrevidaRESUMO
There is a pressing need to identify therapeutic targets in tumors with low mutation rates such as the malignant pediatric brain tumor medulloblastoma. To address this challenge, we quantitatively profiled global proteomes and phospho-proteomes of 45 medulloblastoma samples. Integrated analyses revealed that tumors with similar RNA expression vary extensively at the post-transcriptional and post-translational levels. We identified distinct pathways associated with two subsets of SHH tumors, and found post-translational modifications of MYC that are associated with poor outcomes in group 3 tumors. We found kinases associated with subtypes and showed that inhibiting PRKDC sensitizes MYC-driven cells to radiation. Our study shows that proteomics enables a more comprehensive, functional readout, providing a foundation for future therapeutic strategies.
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Biomarcadores Tumorais/metabolismo , Neoplasias Encefálicas/patologia , Meduloblastoma/patologia , Processamento de Proteína Pós-Traducional , Adolescente , Adulto , Linhagem Celular Tumoral , Criança , Pré-Escolar , Metilação de DNA , Proteína Quinase Ativada por DNA/metabolismo , Feminino , Perfilação da Expressão Gênica , Proteínas Hedgehog/metabolismo , Humanos , Lactente , Masculino , Proteínas Nucleares/metabolismo , Proteoma/metabolismo , Proteômica , Proteínas Proto-Oncogênicas c-myc/metabolismo , Análise de Sequência de RNA , Adulto JovemRESUMO
The Alu element, the most prevalent SINE (short interspersed element) in the human genome, is one of the many RNA-encoding genes that evolved from the 7SL RNA gene. During analysis of the evolution of 7SL-derived RNAs, two distinct evolutionary intermediates capable of self-catalyzed DNA depurination (SDP) were identified. These SDP sequences spontaneously create apurinic sites that can result in increased mutagenesis due to their error-prone repair. This DNA self-depurination mechanism has been shown both in vitro and in vivo to lead to substitution and short frameshift mutations at a frequency that far exceeds their occurrence due to random errors in DNA replication. In both evolutionary intermediates, the same self-depurination sequence overlaps motifs necessary for successful transcription and SRP9/14 (signal recognition particle) binding; hence, mutations in this region could disrupt RNA activity. Yet, the 7SL-derived RNAs that arose from the elements capable of SDP show significant diversity in this region, and every new sequence retains the transcription and SRP9/14-binding motifs, even as it has lost the SDP sequence. While some (but not all) of the mutagenesis can be alternatively attributed to CpG decay, the very fact that the self-depurinating sequences are selectively discarded in all cases suggests that this was evolutionarily motivated to prevent further destructive mutagenesis by the SDP mechanism.